WO2018192496A1 - Procédé et dispositif de génération d'informations de tendance, support de stockage et dispositif électronique - Google Patents

Procédé et dispositif de génération d'informations de tendance, support de stockage et dispositif électronique Download PDF

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WO2018192496A1
WO2018192496A1 PCT/CN2018/083397 CN2018083397W WO2018192496A1 WO 2018192496 A1 WO2018192496 A1 WO 2018192496A1 CN 2018083397 W CN2018083397 W CN 2018083397W WO 2018192496 A1 WO2018192496 A1 WO 2018192496A1
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user behavior
behavior
word
words
similar
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PCT/CN2018/083397
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Chinese (zh)
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赵琳琳
张纪红
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腾讯科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism

Definitions

  • the present invention relates to the field of computers, and in particular to a method and apparatus for generating heat information, a storage medium, and an electronic device.
  • Baidu Index is a data sharing platform based on Baidu's massive netizen behavior data. It is one of the most important statistical analysis platforms in the current Internet and even the entire data age. It has become an important basis for many companies' marketing decisions since the release date.
  • Baidu Index can reflect: how large a keyword is in Baidu's search, the ups and downs of a period of time and related news and public opinion changes, what are the netizens who pay attention to these words, where are they distributed, and which are also searched? Related words, etc., Baidu Index can help users optimize digital marketing campaigns.
  • the related technology is aimed at the index analysis of a single word, and the coverage of the heat information reflected by the analysis result is narrow, which leads to low accuracy of the heat information, and cannot provide accurate data support for digital marketing.
  • Embodiments of the present invention provide a method and apparatus for generating heat information, a storage medium, and an electronic device, so as to at least solve the index analysis of a related word for a single word, and the coverage of the heat information reflected by the analysis result is narrow, thereby causing heat information.
  • a method for generating a heat information includes: acquiring a keyword set, wherein the keyword set includes: a plurality of keywords; and acquiring an extended word set according to the keyword set, wherein the extended
  • the words in the word set include: a plurality of keywords and similar words similar to each of the plurality of keywords; and obtaining target user behavior data matching the words in the expanded word set from the predetermined set of user behavior data
  • the target user behavior data is used to indicate at least the user behavior, the number of times the user behavior is performed, and the behavior type to which the user behavior belongs; and the heat information of each behavior type is generated according to the target user behavior data, wherein the heat information of the behavior type is used. Indicates the heat of the type of behavior.
  • a device for generating heat information including: a first acquiring unit, configured to acquire a keyword set, wherein the keyword set includes: a plurality of keywords; and the second obtaining a unit, configured to obtain an extended word set according to the keyword set, where the words in the extended word set include: a plurality of keywords and similar words similar to each of the plurality of keywords; and a third obtaining unit, Obtaining target user behavior data matching the words in the extended word set from the predetermined user behavior data set, wherein the target user behavior data is at least used to indicate the user behavior, the number of times the user behavior is performed, and the behavior type to which the user behavior belongs; And a generating unit, configured to generate heat information of each behavior type according to the target user behavior data, wherein the heat information of the behavior type is used to indicate the heat of the behavior type.
  • a storage medium wherein the storage medium stores a computer program configured to execute a method of generating heat information in an embodiment of the present invention at runtime.
  • an electronic device comprising a memory and a processor, wherein the memory stores a computer program, the processor being arranged to execute the computer program to perform the embodiment of the present invention Method of generating heat information.
  • the extended word set is obtained according to the keyword set, so that the range covered by the keyword is wider, and then the target user behavior data matching the words in the extended word set is obtained from the predetermined user behavior data set.
  • the purpose of increasing the coverage of the generated heat information is achieved, thereby solving the index analysis of the related technology for a single word, and the heat information reflected by the analysis result.
  • the technical problem of improving the accuracy of the heat information is achieved by the narrower coverage, which leads to a technical problem of lower accuracy of the heat information.
  • FIG. 1 is a schematic diagram of a hardware environment of a method for generating heat information according to an embodiment of the present invention
  • FIG. 2 is a flowchart of a method for generating optional heat information according to an embodiment of the present invention
  • FIG. 3 is a flow chart of constructing a financial index in accordance with a preferred embodiment of the present invention.
  • FIG. 4 is a schematic diagram showing the display of a financial index and an index of each financial product in accordance with a preferred embodiment of the present invention
  • FIG. 5 is a schematic diagram of an apparatus for generating heat information according to an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of another optional heat information generating apparatus according to an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of another optional apparatus for generating heat information according to an embodiment of the present invention.
  • FIG. 8 is a schematic diagram of another optional apparatus for generating heat information according to an embodiment of the present invention.
  • FIG. 9 is a schematic diagram of another optional apparatus for generating heat information according to an embodiment of the present invention.
  • FIG. 10 is a schematic illustration of another alternative heat generation information generating apparatus in accordance with an embodiment of the present invention.
  • FIG. 11 is a schematic diagram of another optional apparatus for generating heat information according to an embodiment of the present invention.
  • FIG. 12 is a schematic diagram of another optional apparatus for generating heat information according to an embodiment of the present invention.
  • FIG. 13 is a structural block diagram of an electronic device according to an embodiment of the present invention.
  • the relative number of changes in the total number of phenomena is an index.
  • the narrow index is to reflect the change in the overall number of complex phenomena.
  • the common index is the stock index (such as the above index), the consumer price index (CPI). ), air index, etc.
  • a method of generating heat information is provided.
  • the method for generating the heat information may be applied to a hardware environment formed by the server 102 and the terminal 104 as shown in FIG. 1 .
  • the server 102 is connected to the terminal 104 through a network.
  • the network includes but is not limited to a wide area network, a metropolitan area network, or a local area network.
  • the terminal 104 is not limited to a PC, a mobile phone, a tablet, or the like.
  • the method for generating the heat information of the embodiment of the present invention may be executed by the server 102, may be executed by the terminal 104, or may be performed by the server 102 and the terminal 104 in common.
  • the method for generating the heat information of the terminal 104 in the embodiment of the present invention may also be performed by a client installed thereon.
  • FIG. 2 is a flowchart of a method for generating optional heat information according to an embodiment of the present invention. As shown in FIG. 2, the method may include the following steps:
  • Step S202 acquiring a keyword set, where the keyword set includes: a plurality of keywords;
  • Step S204 Acquire an extended word set according to the keyword set, where the words in the extended word set include: a plurality of keywords and similar words similar to each of the plurality of keywords;
  • Step S206 acquiring target user behavior data matching the words in the extended word set from the predetermined user behavior data set, wherein the target user behavior data is at least used to indicate the user behavior, the number of times the user behavior is performed, and the behavior to which the user behavior belongs.
  • the target user behavior data is at least used to indicate the user behavior, the number of times the user behavior is performed, and the behavior to which the user behavior belongs.
  • Step S208 generating heat information of each behavior type according to the target user behavior data, wherein the heat information of the behavior type is used to indicate the heat of the behavior type.
  • the extended word set is obtained according to the keyword set, so that the range covered by the keyword is wider, and then the target user behavior matching the words in the extended word set is obtained from the predetermined user behavior data set.
  • the data is used to generate the heat information of each behavior type according to the target user behavior data, thereby achieving the purpose of increasing the coverage of the generated heat information, thereby solving the index analysis of the related technology for a single word, and the heat reflected by the analysis result
  • the technical coverage of the information is narrower, resulting in a lower technical accuracy of the thermal information, thereby achieving the technical effect of improving the accuracy of the thermal information.
  • the keyword set in the embodiment of the present invention may be a set of all the keywords involved in the target domain of the hotspot information to be analyzed, wherein the embodiment of the present invention does not specifically target the target domain.
  • Limited for example, financial field, game field, video field, etc. All keywords involved in the target domain may be classified according to the types of product objects in the target domain, that is, the keyword set may include a subset of keywords corresponding to at least one product object, each keyword The concentration can also include multiple keywords involved in the product object.
  • a keyword set in the financial field may include a keyword subset corresponding to a "stock" financial product ⁇ stock
  • the keyword set in the game field may include a keyword subset corresponding to the "QQ Hyun Dance" game product ⁇ QQ Hyun Dance
  • the above example is only a simple illustration. In practical applications, the number of multiple keywords in the keyword set may be large, so that more accurate hotspot information can be obtained based on a large number of keywords.
  • the embodiment of the present invention may obtain a keyword set by using a method in which a server may filter a keyword related to a target domain of the hotspot information to be analyzed from a large amount of words into a keyword set; or use data collection and The data processing technology pre-collects and saves words related to the target domain of the hotspot information to be analyzed, so as to be directly obtained by the server, which can reduce the system resources consumed by the server to perform data processing, and can optimize the performance of the server system.
  • the keyword set may be obtained in other manners, and is not illustrated here.
  • the embodiment of the present invention may be based on The keyword set obtains a set of extended words.
  • the extended word set may include similar similarities to multiple keywords in the keyword set, in addition to the plurality of keywords in the keyword set. word.
  • the step S204 of acquiring the extended word set according to the keyword set may include steps S2042 to S2044, specifically:
  • Step S2042 Obtain a target similar word similar to each of the plurality of keywords from the similar word set.
  • the similar word set may be pre-generated by Google's open source tool word2vec, and the similar word set may include a plurality of similar phrases, and each similar phrase includes at least two similar similar words.
  • the alternative embodiment may use a similar word set to acquire words similar to each keyword in the keyword set as target similar words, and then combine the target similar words with a plurality of keywords in the keyword set to form a set of extended words.
  • the step S2042: acquiring the target similar words similar to each of the plurality of keywords from the similar word set may include:
  • step S20422 For each keyword in the keyword set, the following step S20422 may be performed, wherein each keyword may be regarded as a current keyword when performing step S20422:
  • Step S20422 searching for a similarity word similar to the current keyword in the similar word set of the current keyword, wherein the vector distance between the target similar word and the current keyword similar to the current keyword is less than or equal to a predetermined threshold.
  • the method for calculating the distance between the word vectors is not limited in the embodiment of the present invention. Any method that can calculate the distance between the word vectors belongs to the protection scope of the embodiment of the present invention.
  • the searched one or more target similar words and the plurality of keywords in the keyword set may be used to form the extended word set.
  • the alternative embodiment utilizes the distance between the word vectors to determine a target similar word that is similar to the keyword in the key word set, and can achieve the purpose of improving the accuracy of the determined target similar word.
  • a plurality of keywords in the keyword set and similar words similar to the keywords are combined into a set of extended words, and the hotspot information of the target domain is generated by using the expanded word set, so that the accuracy of the heat information can be improved.
  • the optional embodiment may further perform the following steps:
  • step S2044 the invalid words are filtered out among the plurality of keywords and the target similar words to obtain an expanded word set.
  • the optional embodiment may use the following steps S20442 to S20446 to filter out the invalid words in the extended word set, specifically:
  • Step S20442 displaying multiple keywords and target similar words
  • Step S20444 receiving a filtering instruction, where the filtering instruction carries an invalid word that needs to be filtered out;
  • Step S20446 in response to the filtering instruction, filtering the invalid words in the plurality of keywords and the target similar words to obtain the expanded word set.
  • the filtering instruction may carry an invalid word that needs to be filtered out, wherein the number of invalid words may be one or multiple, and it should be noted that the filtering instruction may be a user.
  • the instructions generated according to the actual requirements may also be filtering instructions generated according to a predetermined filtering policy, which is not specifically limited herein.
  • the server may display the multiple keywords in the extended word set and the similar target similar words to the user, and the user may select whether to trigger the filtering instruction according to actual needs, and the user selects to trigger the filtering instruction.
  • the server may respond to the invalid words that need to be filtered from the filtering instructions from multiple keywords and similar target similar words, so as to be accurately expanded. Word collection.
  • a shares ⁇ is expanded to ⁇ stock
  • the "stock type” and "stock” in the expanded word set are words with inclusive relationship, which can be eliminated in the data mining, and the "shares" are keywords that may introduce noise to the subsequent mining data.
  • the server response filtering instruction may filter the invalid words from the plurality of keywords and the target similar words one by one, and each time an invalid word is filtered, the extended word set displayed to the user is updated once to facilitate the user.
  • the filtering progress can be clearly grasped, and whether the filtering is again performed or the filtering is stopped according to the actual demand, thereby achieving the purpose of facilitating flexible control by the user.
  • the optional embodiment can improve the accuracy of the extended word set by performing invalid word filtering on the expanded word set, thereby improving the accuracy of the heat information generated according to the expanded word set.
  • the predetermined set of user behavior data may include data of a large amount of user behavior performed by the user in the target domain of the heat information to be analyzed, for example, the predetermined user behavior data set of the financial domain may include the user. Involving all financial activities on the website, such as reading financial news, forwarding and sharing related content, installing financial applications, and joining financial interest groups.
  • the embodiment may obtain target user behavior data that matches the words in the extended word set from the predetermined user behavior data set, where the target user behavior data may be at least used to indicate the user.
  • the target user behavior data in the embodiment of the present invention may also be used to indicate the type of the execution object of the user behavior, and the user, in addition to the indication information listed above, the behavior of the user behavior.
  • Information such as the execution time of the behavior and the frequency of execution of the user's behavior.
  • the behavior is recorded as [financial behavior
  • the stock is a financial product type; for example, if a user installs the "Lu Jin" APP, the behavior is recorded as [Financial Behavior
  • the target user behavior data may be user behavior data in the predetermined user behavior data set that matches the words in the extended word set, where the matching may be understood as the user behavior indicated by the target user behavior data.
  • the behavior type matches the words in the extended word set, and may be understood as: the behavior information used to indicate the user behavior or the behavior type in the target user behavior data may include words in the extended word set; or the target user behavior
  • the behavior information used to indicate the user behavior or the type of behavior in the data may include words related to words in the expanded word set, where the correlation may be understood as similar or have some association relationship.
  • step S206 obtains target user behaviors that match the words in the expanded word set from the predetermined set of user behavior data.
  • the data may include: step S2062, searching for the target user behavior data in the user behavior data set, wherein the user behavior or behavior type indicated by the target user behavior data matches the words in the extended word set, specifically, the target user behavior data
  • the behavior information used to indicate the user's behavior or behavior type may include words in the expanded word set, or words related to the words in the expanded word set.
  • the set of extended words is ⁇ stock stocks
  • the optional embodiment can make the relevance of the found target user behavior data and the words in the extended word set by searching the predetermined user behavior data for the user behavior data matching the words in the expanded word set as the target behavior data. Higher, which in turn makes the heat information generated according to the target user behavior data more accurate.
  • the extended word set in the embodiment of the present invention may include a plurality of words, and the target user behavior data matching each word may be one or more, wherein, multiple targets
  • the types of behavior indicated by each target user behavior data in the user behavior data may all be the same, may be partially the same, or may be different.
  • the embodiment of the present invention may separately calculate the heat information of each behavior type according to the target user behavior data, wherein the heat information of each behavior type may be used to indicate the behavior type. The heat.
  • generating the heat information of each of the behavior types according to the target user behavior data in step S208 may include:
  • Step S2082 calculating a heat index of each of the behavior types according to the target user behavior data, wherein the heat index of the behavior type is used to indicate heat information of the behavior type, and the heat index of the behavior type belongs to
  • the number of times the user behavior of the behavior type is performed is the product of the weight of the user behavior pre-assigned to the behavior type.
  • the heat index of the behavior type can be used to indicate the heat information of the behavior type, wherein the greater the heat index of the behavior type, the higher the heat of the behavior type, and the smaller the heat index of the behavior type indicates the behavior type. The lower the heat.
  • the heat index of the behavior type the number of times the user behavior is performed ⁇ the weight assigned to the user behavior in advance, wherein the weight assigned to the user behavior may be According to the actual needs, there is no specific limit here.
  • the heat index of the behavior type Where N is the number of user behaviors belonging to the behavior type, Ci is the number of times the i-th user behavior is performed, and Wi is the weight assigned to the i-th user behavior in advance.
  • the user behavior of the behavior type belonging to financial behavior is: [financial behavior
  • once], wherein the number of times the user behavior is executed is 1, and the weight of the behavior assigned to the user in advance is 1.9, then the heat index of the behavior type belonging to financial behavior is 1 ⁇ 0.5+1 ⁇ 1.9 2.4.
  • the optional embodiment may further include:
  • Step S209 displaying the heat information of each behavior type in the predetermined time period.
  • the heat information of these behavior types can be compared and displayed, so that the user can intuitively and clearly analyze the heat of each behavior type and the behavior types of each behavior.
  • Heat difference The optional embodiment does not specifically limit the manner in which the heat information of the behavior type is displayed.
  • the heat information of multiple behavior types may be displayed in a curve comparison chart or in a histogram format.
  • the optional embodiment may also display the heat information of each behavior type in a predetermined time period, wherein the predetermined time period may be set according to actual analysis, which is not specifically limited herein. Clearly analyze the purpose of the heat trend of each behavior type.
  • the optional embodiment may further include:
  • Step S210 media resources matching the heat information of each behavior type are placed in a predetermined application.
  • the optional embodiment may determine a media resource that matches the media resource.
  • the media resource may include, but is not limited to, an advertisement, an audio, a video, and the like.
  • the optional embodiment may deliver a media resource that matches the heat information of each behavior type in a predetermined application, wherein the optional embodiment does not specifically limit the type of the predetermined application, for example, a browser application. , video client applications, game client applications, wealth management client applications. It should be noted that the optional embodiment does not specifically limit the delivery manner of the media resource that matches the heat information of each behavior type.
  • the media resource may be delivered when the application is started, or may be applied. Delivered at scheduled intervals after startup.
  • the optional embodiment is based on the heat information of each behavior type, and the media resources matched with the predetermined application are used to improve the user's interest in the media resources to be served, thereby increasing the exposure of the media resources being served.
  • the purpose of the rate is based on the heat information of each behavior type, and the media resources matched with the predetermined application are used to improve the user's interest in the media resources to be served, thereby increasing the exposure of the media resources being served. The purpose of the rate.
  • the method for generating the heat information of the embodiment of the present invention can be applied to heat analysis in various fields, such as the financial field, the game field, the video field, and the like.
  • the following preferred embodiment further describes the method for generating the heat information according to the embodiment of the present invention by taking the heat analysis in the financial field as an example.
  • the present invention also provides a preferred embodiment that provides a social financial index construction scheme to track the hot trend of the financial industry.
  • the social financial index in this program is based on the Internet social products based on massive netizen behavior data to reflect the user's metrics in the financial field, including user financial heat index, user securities heat index, user real estate heat index, insurance heat index, etc. .
  • the financial index can tell you the overall trend, geographical distribution, and population characteristics of the industry; it can also be seen which trends in the segmentation.
  • the social financial index is based on the behavior data of massive netizens on many products, and the keyword set is used as a financial word set by word2vec technology.
  • the financial term covers products such as securities, wealth management, insurance, loans, and real estate.
  • the keyword behavior matching and behavior mining are used to construct a financial behavior set of the user on each financial product, and the financial behavior set includes information such as product type, behavior type, behavior frequency, and behavior time.
  • the financial index of Beijing such as the financial index after 70/80, such as the financial index of the master's degree.
  • the financial index is calculated on a daily basis, and the data is accumulated for a period of time to get an overall trend for a period of time.
  • the social financial index includes user financial index, financial management index, securities index, insurance index, real estate index, and each index supports subdivision, such as stock index, each p2p product index.
  • the financial index reflects the hot trend of financial behavior of users on social platforms, and provides a big data basis for Internet financial advertisers to advertise on social media, which can predict the number of audiences and the quality of the crowd.
  • the execution process of the financial index construction scheme can be as shown in FIG. 3, and specifically includes the following steps:
  • Step S302 constructing a financial word set.
  • the seed word set S is given manually.
  • the word set of "stock” is as follows (the following is a simple example, the actual word set will be much larger): ⁇ stock
  • Step S304 expanding the financial lexicon based on the similar vocabulary (the similar vocabulary can be generated using google's open source tool word2vec).
  • the expansion steps are as follows:
  • dis(e(Si) )-Si) ⁇ n ⁇ , dis(e(Si)-Si) represents the distance between two word vectors.
  • Manual annotation generates a target word set D.
  • the invalid word filtering is realized by manual labeling, and the target word set D finally used in data mining is obtained.
  • the financial vocabulary ⁇ stock
  • Step S306 constructing a user financial behavior set.
  • the financial behavior set is filtered out from the massive user behavior data through keyword mining.
  • the financial behavior set covers all financial behaviors of users on social networking sites: reading financial news, forwarding and sharing related content, installing financial APPs (such as Ping An Securities, self-selected stocks, etc.), and joining financial interest groups. For example, if a user searches for a keyword xx stock, the behavior is recorded as [financial behavior
  • step S308 a financial index is constructed.
  • the weighted times of each financial product are summarized as the index of the day.
  • the stock index is calculated as follows:
  • Istock is the stock index
  • the number of behaviors of Ci is the weight
  • Wtype can be the weight assigned according to the artificial experience. For example, the user reads the financial article with a weight of 1, and the forwarding financial article is 2.
  • Step S310 showing the trend of the accumulated financial index.
  • the financial index can be generated on a daily basis, and a cumulative period of time can get a trend of the financial index for a period of time.
  • the trend of the financial index and the index of multiple financial products can be compared as shown in Figure 4.
  • the financial index can reflect the hot trend of a financial product and the degree of concern, but also can be seen The difference in the heat of financial products.
  • the financial index reflects the trend of financial enthusiasm on social platforms, providing a reliable basis for financial products to advertise on social media, providing predictable basis for the number and quality of audiences, and providing financial services to advertisers on social platforms. Product activity and trends.
  • the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware, but in many cases, the former is A better implementation.
  • the technical solution of the present invention which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a cell phone, a computer, a server, or a network device, etc.) to perform the methods described in various embodiments of the present invention.
  • FIG. 5 is a schematic diagram of an apparatus for generating heat information according to an embodiment of the present invention. As shown in FIG. 5, the apparatus may include:
  • the first obtaining unit 22 is configured to acquire a keyword set, where the keyword set includes: a plurality of keywords; and the second obtaining unit 24 is configured to obtain the extended word set according to the keyword set, where the words in the extended word set are
  • the method includes: a plurality of keywords and similar words similar to each of the plurality of keywords; and a third obtaining unit 26, configured to obtain, from the predetermined set of user behavior data, a target that matches the words in the expanded word set
  • the user behavior data wherein the target user behavior data is used to indicate at least the user behavior, the number of times the user behavior is performed, and the behavior type to which the user behavior belongs;
  • the generating unit 28 is configured to generate the heat information of each behavior type according to the target user behavior data. Among them, the heat information of the behavior type is used to indicate the heat of the behavior type.
  • first obtaining unit 22 in this embodiment may be used to perform step S202 in the first embodiment of the present application.
  • the second obtaining unit 24 in this embodiment may be used to perform the method in the first embodiment of the present application.
  • the third obtaining unit 26 in this embodiment may be used to perform step S206 in the embodiment 1 of the present application.
  • the generating unit 28 in this embodiment may be used to perform step S208 in the embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the second obtaining unit 24 may include: an obtaining module 242, configured to acquire, from the similar word set, a target similar to each of the plurality of keywords. a word filtering module 244, configured to filter out invalid words in a plurality of keywords and target similar words to obtain an expanded word set.
  • the obtaining module 242 in this embodiment may be used to perform step S2042 in the first embodiment of the present application.
  • the filtering module 244 in this embodiment may be used to perform step S2044 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the obtaining module 242 may include: a searching submodule 2422, configured to perform, for each keyword, the following steps, wherein each keyword is regarded as a current keyword Searching for a similarity word similar to the current keyword in the similar word set of the current keyword, wherein the vector distance between the target similar word and the current keyword similar to the current keyword is less than or equal to a predetermined threshold.
  • search sub-module 2422 in this embodiment may be used to perform step S20422 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the filtering module 244 may include: a display submodule 2442 for displaying a plurality of keywords and target similar words; and a receiving submodule 2444 for receiving filtering instructions, wherein The filtering instruction carries the invalid words that need to be filtered out; the response sub-module 2446 is configured to filter the invalid words in the plurality of keywords and the target similar words in response to the filtering instruction to obtain the expanded word set.
  • the display sub-module 2442 in this embodiment may be used to perform step S20442 in Embodiment 1 of the present application.
  • the receiving sub-module 2444 in this embodiment may be used to perform step S20444 in Embodiment 1 of the present application.
  • the response sub-module 2446 in this embodiment may be used to perform step S20446 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the third obtaining unit 26 may include: a searching module 262, configured to search for target user behavior data in the user behavior data set, where the target user behavior data indicates The user behavior or behavior type matches the words in the extension word set.
  • searching module 262 in this embodiment may be used to perform step S2026 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the matching of the user behavior or behavior type indicated by the target user behavior data found by the searching module 262 with the words in the extended word set includes: indicating user behavior or behavior in the target user behavior data.
  • the type of behavior information includes: words in the set of extended words, or words related to words in the set of extended words.
  • the generating unit 28 may include: a calculating module 282, configured to calculate a heat index of each of the behavior types according to the target user behavior data, wherein the behavior The heat index of the type is used to indicate the heat information of the behavior type, the heat index of the behavior type is the number of times the user behavior of the behavior type is performed and the weight of the user behavior pre-allocated to the behavior type.
  • a calculating module 282 configured to calculate a heat index of each of the behavior types according to the target user behavior data, wherein the behavior The heat index of the type is used to indicate the heat information of the behavior type, the heat index of the behavior type is the number of times the user behavior of the behavior type is performed and the weight of the user behavior pre-allocated to the behavior type.
  • calculation module 282 in this embodiment may be used to perform step S2082 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the apparatus may further include: a display unit 29, configured to display each of the predetermined time periods after generating the heat information of each behavior type according to the target user behavior data.
  • the heat information of the behavior type may be displayed using a display unit 29, configured to display each of the predetermined time periods after generating the heat information of each behavior type according to the target user behavior data. The heat information of the behavior type.
  • the display unit 29 in this embodiment may be used to perform step S209 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the apparatus may further include: a placing unit 210, configured to: in the predetermined application, after generating the heat information of each behavior type according to the target user behavior data; The media resource for each behavior type's heat information matches.
  • the delivery unit 210 in this embodiment may be used to perform step S210 in Embodiment 1 of the present application.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the foregoing modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the foregoing embodiments. It should be noted that the foregoing module may be implemented in a hardware environment as shown in FIG. 1 as part of the device, and may be implemented by software or by hardware.
  • the purpose of increasing the coverage of the generated heat information can be achieved, and the index analysis of the related words for a single word is solved, and the coverage of the heat information reflected by the analysis result is narrower, thereby causing the accuracy of the heat information to be more accurate.
  • Low technical problems thus achieving the technical effect of improving the accuracy of the heat information.
  • an electronic device for implementing the method for generating the heat information described above is further provided.
  • FIG. 13 is a structural block diagram of an electronic device according to an embodiment of the present invention.
  • the electronic device may include: one or more (only one shown) processor 201 and memory 203, where A computer program may be stored in the memory 203, and the processor 201 may be configured to execute the computer program to execute the method of generating the heat information of the embodiment of the present invention.
  • the memory 203 can be used to store a computer program and a module, such as a method for generating heat information in the embodiment of the present invention, and a program instruction/module corresponding to the device.
  • the processor 201 is configured to run the software program stored in the memory 203 and Modules, thereby performing various functional applications and data processing, that is, implementing the above-described method of generating heat information.
  • Memory 203 can include high speed random access memory, and can also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory.
  • memory 203 can further include memory remotely located relative to processor 201, which can be connected to the terminal over a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
  • the electronic device may further include: a transmission device 205 and an input and output device 207.
  • the transmission device 205 is configured to receive or transmit data via a network. Specific examples of the above network may include a wired network and a wireless network.
  • the transmission device 205 includes a Network Interface Controller (NIC) that can be connected to other network devices and routers via a network cable to communicate with the Internet or a local area network.
  • the transmission device 205 is a Radio Frequency (RF) module for communicating with the Internet wirelessly.
  • NIC Network Interface Controller
  • RF Radio Frequency
  • the memory 203 is used to store a computer program.
  • the processor 201 may be configured to run a computer program stored in the memory 203 to perform the steps of: acquiring a set of keywords, wherein the set of keywords comprises: a plurality of keywords; acquiring a set of extended words according to the set of keywords, wherein the The words in the word set include: a plurality of keywords and similar words similar to each of the plurality of keywords; and obtaining target user behavior data matching the words in the expanded word set from the predetermined set of user behavior data
  • the target user behavior data is used to indicate at least the user behavior, the number of times the user behavior is performed, and the behavior type to which the user behavior belongs; and the heat information of each behavior type is generated according to the target user behavior data, wherein the heat information of the behavior type is used. Indicates the heat of the type of behavior.
  • the processor 201 is further configured to: obtain a target similar word similar to each of the plurality of keywords from the similar word set; filter out the invalid word in the plurality of keywords and the target similar word, and obtain Extended word collection.
  • the processor 201 is further configured to perform the following steps: for each keyword, performing the following steps, wherein each keyword is regarded as a current keyword: searching for a similar word set in the current keyword similar to the current keyword The target similarity word, wherein the vector distance between the target similar word and the current keyword similar to the current keyword is less than or equal to a predetermined threshold.
  • the processor 201 is further configured to: perform multiple steps of: displaying a plurality of keywords and target similar words; receiving a filtering instruction, wherein the filtering instruction carries an invalid word that needs to be filtered; and responding to the filtering instruction, the multiple keywords and the target are similar Filter out invalid words in the word to get a set of extended words.
  • the processor 201 is further configured to: perform target user behavior data in the user behavior data set, wherein the user behavior or behavior type indicated by the target user behavior data matches the words in the extended word set, and the target user behavior data
  • the behavior information used to indicate the user behavior or behavior type includes: words in the expanded word set, or words related to the words in the expanded word set.
  • the processor 201 is further configured to: calculate a heat index of each of the behavior types according to the target user behavior data, wherein a heat index of the behavior type is used to indicate heat information of the behavior type,
  • the heat index of the behavior type is the product of the number of times the user behavior of the behavior type is performed and the weight of the user behavior pre-assigned to the behavior type.
  • the processor 201 is further configured to perform the step of displaying the heat information of each behavior type within a predetermined time period after generating the heat information of each behavior type according to the target user behavior data.
  • the processor 201 is further configured to perform the following steps: after generating the heat information of each behavior type according to the target user behavior data, the media resources matching the heat information of each behavior type are served in the predetermined application.
  • a scheme for generating heat information is provided.
  • the range covered by the keywords is wider, and then the target user behavior data matching the words in the expanded word set is obtained from the predetermined set of user behavior data, so as to be based on the target user behavior.
  • the data generates the heat information of each behavior type, and achieves the purpose of increasing the coverage of the generated heat information, thereby solving the index analysis of the related technology for a single word, and the coverage of the heat information reflected by the analysis result is narrow, thereby causing The technical problem of lower accuracy of the heat information, thereby achieving the technical effect of improving the accuracy of the heat information.
  • FIG. 13 is merely illustrative, and the electronic device can be a smart phone (such as an Android mobile phone, an iOS mobile phone, etc.), a tablet computer, a palmtop computer, and a mobile Internet device (MID). Terminal equipment such as PAD.
  • FIG. 13 does not limit the structure of the above electronic device.
  • the electronic device may also include more or fewer components (such as a network interface, display device, etc.) than shown in FIG. 13, or have a different configuration than that shown in FIG.
  • a storage medium stores a computer program, and the computer program may be configured to execute a method for generating the heat information at runtime.
  • the foregoing storage medium may be located on at least one of the plurality of network devices in the network shown in the foregoing embodiment.
  • the storage medium is arranged to store program code for performing the following steps:
  • target user behavior data that matches the words in the extended word set from the predetermined set of user behavior data, where the target user behavior data is used to at least indicate the user behavior, the number of times the user behavior is performed, and the behavior type to which the user behavior belongs. ;
  • the storage medium is further configured to store program code for performing the following steps: obtaining a target similar word similar to each of the plurality of keywords from the similar word set; in the plurality of keywords and targets Filter out invalid words in similar words to get a set of extended words.
  • the storage medium is further arranged to store program code for performing the following steps: for each keyword, the following steps are performed, wherein each keyword is treated as a current keyword: a similar word at the current keyword A target similar word similar to the current keyword is searched in the set, wherein a vector distance between the target similar word and the current keyword similar to the current keyword is less than or equal to a predetermined threshold.
  • the storage medium is further configured to store program code for performing the following steps: displaying a plurality of keywords and target similar words; receiving a filtering instruction, wherein the filtering instruction carries an invalid word that needs to be filtered; the response filtering instruction Filter out invalid words in multiple keywords and target similar words to get a set of extended words.
  • the storage medium is further configured to store program code for performing the following steps: finding target user behavior data in the user behavior data set, wherein the user behavior or behavior type and extension word set indicated by the target user behavior data
  • the word matching in the target user behavior data for indicating the user behavior or the behavior type includes: a word in the extended word set, or a word related to the word in the expanded word set.
  • the storage medium is further configured to store program code for performing a step of: calculating a heat index for each of the behavior types based on the target user behavior data, wherein the heat index of the behavior type is used to indicate The popularity information of the behavior type, the heat index of the behavior type is a product of the number of times the user behavior of the behavior type is performed and the weight of the user behavior pre-allocated to the behavior type.
  • the storage medium is further configured to store program code for performing the following steps: after generating the heat information for each behavior type based on the target user behavior data, displaying the heat information for each behavior type within the predetermined time period.
  • the storage medium is further configured to store program code for performing the following steps: after generating the heat information of each behavior type according to the target user behavior data, delivering the heat information with each behavior type in the predetermined application Matching media assets.
  • the foregoing storage medium may include, but not limited to, a USB flash drive, a Read-Only Memory (ROM), a Random Access Memory (RAM), a mobile hard disk, and a magnetic memory.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • a mobile hard disk e.g., a hard disk
  • magnetic memory e.g., a hard disk
  • the integrated unit in the above embodiment if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in the above-described computer readable storage medium.
  • the technical solution of the present invention may contribute to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium.
  • a number of instructions are included to cause one or more computer devices (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the disclosed client may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, unit or module, and may be electrical or otherwise.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

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Abstract

L'invention concerne un procédé et un dispositif de génération d'informations de tendance, un support de stockage et un dispositif électronique. Le procédé consiste à : acquérir un ensemble de mots-clés, l'ensemble de mots-clés comprenant de multiples mots-clés (S202) ; acquérir un ensemble de mots étendu en fonction de l'ensemble de mots-clés, l'ensemble de mots étendu comportant des mots comprenant : des mots-clés multiples et des mots similaires à chacun des mots-clés dans les multiples mots-clés (S204) ; acquérir, à partir d'un ensemble de données de comportement d'utilisateur prédéfini, des données de comportement d'utilisateur cibles correspondant aux mots de l'ensemble de mots étendu, les données de comportement d'utilisateur cibles étant au moins utilisées pour indiquer un comportement d'utilisateur, un certain nombre d'exécutions de comportement d'utilisateur et un type de comportement auquel appartient le comportement d'utilisateur (S206) ; et générer, en fonction des données de comportement d'utilisateur cible, les informations de tendance de chaque type de comportement, les informations de tendance du type de comportement étant utilisées pour indiquer la popularité d'un type de comportement (S208). Le procédé et le dispositif peuvent servir à résoudre le problème technique dans l'état de la technique selon lequel les informations de tendance reflétées par les résultats d'analyses d'index de mots uniques ont une faible portée, ce qui réduit la précision des informations de tendance.
PCT/CN2018/083397 2017-04-20 2018-04-17 Procédé et dispositif de génération d'informations de tendance, support de stockage et dispositif électronique WO2018192496A1 (fr)

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